Text Classification
Transformers
PyTorch
TensorBoard
deberta-v2
Generated from Trainer
Eval Results (legacy)
Instructions to use Emanuel/twitter-emotion-deberta-v3-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Emanuel/twitter-emotion-deberta-v3-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Emanuel/twitter-emotion-deberta-v3-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Emanuel/twitter-emotion-deberta-v3-base") model = AutoModelForSequenceClassification.from_pretrained("Emanuel/twitter-emotion-deberta-v3-base") - Notebooks
- Google Colab
- Kaggle
Align label mapping with emotion dataset
#1
by lewtun HF Staff - opened
Hi there, your model is using a default label mapping. Accept this PR to align the label mapping with the emotion dataset this model was trained on. This will enable your model to be evaluated by Hugging Face's automatic model evaluator
Sure, thank you, Lewis :)
Emanuel changed pull request status to merged
You're welcome π€!